Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\ub0C (mean = 3.0 \ub1 2.1\ub0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \ub1 2.3\ub0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler ( 120.7 \ub1 2.3\ub0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Sensitivity and uncertainty analysis of the carbon and water fluxes at the tree scale in<i>Eucalyptus</i>plantations using a metamodeling approach

Understanding the consequences of changes in climatic and biological drivers on tree carbon and water fluxes is essential in forestry. Using a metamodeling approach, sensitivity and uncertainty analyses were carried out for a tree-scale model (MAESPA) to isolate the effects of climate, morphological and physiological traits, and intertree competition on the absorption of photosynthetically active radiation (APAR), gross primary production (GPP), transpiration (TR), light use efficiency (LUE), and water use efficiency (WUE) in clonal Eucalyptus plantations. The metamodel predicting daily TR was validated using one year of sap flow measurements and showed close agreement with the measurements (mean percentage error = 11%, n = 2155). Simulations showed that APAR, GPP, and TR were very sensitive to the tree morphology and to a competition index representing its local environment. LUE and WUE were, in addition, very sensitive to the natural variability of the physiological leaf and root parameters. A maximum percentage error of 10% in these parameters leads to 18%, 17%, 16%, 9%, and 18% uncertainty for APAR, GPP, TR, LUE, and WUE, respectively. The uncertainties in TR were highest for the smallest trees. This study highlighted the need to take account of the spatial and temporal variability of tree traits and environmental conditions for simulations at the tree scale

Infuence of rubber trees on leaf-miner damage to coffee plants in an agroforestry system.

The coffee leaf-miner (CLM) (Leucoptera coffeella Guérin-Mèneville; Lepidoptera: Lyonetiidae), the main pest of coffee plants, occurs widely throughout the Neotropics where it has a significant, negative economic and quantitative impact on coffee production. This study was conducted in a rubber tree/coffee plant interface that was influenced by the trees to a varying degrees depending on the location of the coffee plants, i.e. from beneath the rubber trees, extending through a range of distances from the edge of the tree plantation to end in a coffee monocrop field. The most severe damage inflicted on coffee plants by the CLM (number of mined leaves) from April, which marks the start of the water deficit period, until September 2003 was in the zone close to the rubber trees, whereas the damage inflicted on plants in the monocropped field was comparable to that on coffee plants grown directly beneath the rubber trees, which received about 25-40 % of the available irradiance (Ir-available irradiation at a certain position divided by the irradiation received in full sunlight, i.e. in the monocrop). From May until July damage caused by the CLM nearly doubled in each month. In midwinter (July), the damage decreased perceptibly from the tree edge toward the open field. From September onward, with the rising air temperatures CLM damage in the coffee monocrop started to increase. Based on these results, we conclude that coffee plants grown in the full sun incurred the most damage only at the end of winter, with warming air temperatures. Coffee plants grown in shadier locations (25-40 % Ir) were less damaged by the CLM, although a higher proportion of their leaves were mined. The rubber trees probably acted as a shelter during the cold autumn and winter seasons, leading to greater CLM damage over a distance outside the rubber tree plantation that was about equal to the height of the trees. Future studies should attempt to relate leaf hydric potential to pest attack in field conditions. More rigorous measurements of shade conditions could improve our understanding of the relationship of this factor to CLM attack.Published online: 5 October 2013

Modelling eucalyptus biomass production at regional scale in Brazil.

Among forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropicalhardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1.Wide differences of biomass production were observed among neighboring stands representingchallenges to forestry companies to spatially estimate biomass yield in large plantation zones.The first objective of the present research was to modify the carbon allocation scheme in theprocess-based model Generic Decomposition And Yield Model (G?DAY), to better capture thespatial variability in growth rates of Eucalyptus as influenced by environmental constraints suchas water stress. The model was parametrized and tested using experimental and long termcommercial datasets in the state of S ?ao Paulo Brazil. Measured data included several variablesof carbon and water fluxes and carbon stock. The calibrated model produced accurate predictionof the carbon key variables such as leaf area index, stem biomass, and gross primary productionand water related variables such as plant available water and evapotranspiration. Simulating thespatial variability among commercial Eucalyptus stands at landscape scale showed reasonableprediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This couldpartially be attributed to spatial soil data differences used at regional scales which came fromthe Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testingthe soil data with the use of soil type map crossed with soil profile measurements is expectedto improve the soil information for higher accuracy of stem simulation at landscape to regionalscale